Social Network Analysis
I am currently working on releasing introductory online courses on social network analysis (in both English and German language). Drop me a line if I should keep you up to date.
In this course, you will learn (amongst others)…
– …about the learning goals of this course on social network analysis (SNA).
– …why social network analysis is receiving so much interest these days—and why it will pay off for you to learn about it.
– …about the general perspective that social network analysis takes and how this perspective is different or novel.
– …about how we can define the nature of social networks.
– …about social networks by thinking about examples of your own life that may be conceptualized as a (social) network.
– …about a central concept of social network analysis: nodes, which are also called vertices or actors.
– …about modes and the disctinction between one-mode networks and two-mode networks.
– …about another important concept of social network analysis: egdes, which are also called ties or arcs or relationships.
– …about how you may classify differnt types of networks.
– …how networks are made up by vertices and edges.
– …about the difference between sociocentric and egocentric networks in social network analysis.
– …about what types of research question are possible to answer using social network analysis.
– …about the different units of analysis that you may investigate using social network analysis.
– …about the boundary specification problem; a very important challenge in any social network study.
– …about theorizing within social network studies.
– …about the key features of social capital theory.
– …about the key features of cognitive social structures.
– …about the key features of balance theory.
– …about the key features of homophily.
– …about the quality of relational data that we need for social network analysis.
– …about the specificities of collecting quantitative network data via a survey.
– …that ethical considerations are especially important when conducting social network analysis.
– …about two major ways of storing quantitative network data: the matrix format and the edgelist format.
– …how to present quantitative data in different formats (edgelist, matrix, and the visual representation) and how to prepare your data accordingly.
– …about nodal degree, a very basic put important centrality metric frequently used in social network analysis.
– …about betweenness, an often used metric for centrality or brokerage in networks.
– …about closeness, an indicator for distance between one node and the rest of the network.
– …where to download the open source software Gephi, which we will use for network visualization.
– …how to navigate in Gephi.
– …to calculate key metrics of social network analysis in Gephi.
– …about how to apply layouting algorithms in Gephi.
– …how to change the appearance of your network graph based on previously calculated metrics.
– …where to download the software Vennmaker, which we will use for network data collection.
– …how to navigate in VennMaker and how this software may help you in collection relational data.
Datasets (Link): Gephi @ GitHub